Solar cell performance simulation method based on FDTD solution

Abstract

The invention discloses a solar cell performance simulation method based on FDTD (Frequency Division Time Division) solution, which comprises the following steps of: 1, looking up optical parameters of materials in a solar cell, and inputting the optical parameters into a material library; 2, establishing an optical model of the solar cell; 3, setting a simulation area and positions and types of refraction and reflection monitors; light intensity and wavelength of an incident source are set according to sunlight; 4, setting applied boundary conditions, and setting grid precision; 5, establishing a complete solar cell optical model; step 6, carrying out simulation calculation on the performance of the crystalline silicon solar cell, and analyzing carrier generation rate and short-circuit current density factors; 7, performing statistical analysis on all calculation results in the step 6, and calculating refraction, reflectivity, carrier generation rate and short-circuit current density factors of the solar cell; according to the invention, the problems of unclear cell efficiency influence factors, incomplete optical properties and small dimensions are solved from the microscopic perspective.

Description

Technical Field

[0001] The present invention relates to the field of solar cells, and in particular to a method for simulating solar cell performance based on FDTD solution. Background Art

[0002] With the development and progress of society, the problem of climate change has become increasingly prominent worldwide. Building energy consumption accounts for a large proportion of total energy consumption. By strengthening the application of renewable energy in buildings, the problem of high fossil energy can be effectively alleviated. The application of photovoltaic modules in the form of building components can provide a more sustainable development path for the construction industry. Improving the photovoltaic conversion efficiency of solar cells is the core factor in promoting the integration of photovoltaic buildings, while reducing the cost of photovoltaic systems and reducing the investment payback period. Reduce the carbon emissions of the main body of the building. The existing efficiency improvement and structural optimization of solar cells in photovoltaic modules are mainly concentrated in laboratories and factories. There are few methods for simulating the performance optimization of solar cells from internal mechanisms. The main reason is that there are few related software applications for simulating the mechanism of efficiency loss in batteries. At present, the software for solar cell performance simulation includes SCAPS-1D, PC1D, COMSOL, FDTD-solution, etc. SCAPS-1D obtains the efficiency of solar cells by setting factors such as carrier mobility, defect density, and interface defects, and focuses on the influence of internal parameters of solar cells on cell efficiency in a one-dimensional environment. PC1D factors are less discussed and have limited performance. COMSOL has unique advantages in the interaction of multiple physical fields (such as electric fields, magnetic fields, thermal fields, etc.). Compared with the above simulation software, FDTD-solution has a higher simulation effect for complex electromagnetic fields, is more efficient in dealing with high-frequency electromagnetic field problems, has a shorter calculation time, and can analyze the influence of structures on light fields in detail, and has unique advantages in simulating characteristics such as light propagation, scattering, and absorption. Summary of the invention

[0003] The purpose of the present invention is to overcome the above-mentioned shortcomings and provide a solar cell performance simulation method based on FDTD solution, which solves the problems of unclear factors affecting cell efficiency, incomplete optical properties and small dimensions from a microscopic perspective, and provides a feasible solution for improving the efficiency of solar cells.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: a solar cell performance simulation method based on FDTD solution, which includes the following steps: Step 1, look up the optical parameters of materials in solar cells and input them into the material library; Step 2, using the determined optical parameters as known numbers and based on a default crystalline silicon photovoltaic cell structure, an optical model of the solar cell is established; Step 3, according to the size of the solar cell, set the simulation area around the solar cell, the position and type of the refraction and reflection monitor; set the incident light intensity and wavelength according to the sunlight; Step 4, according to the size of the solar cell, set the applied boundary conditions and set the grid accuracy; Step 5, respectively loading the monitor and boundary condition parameters set in steps 3 and 4 into the optical model of the solar cell established in step 2 to establish a complete solar cell optical model; Step 6, based on the complete solar cell optical model established in step 5 and based on the monitor results, simulate and calculate the performance of the crystalline silicon solar cell, and analyze the carrier generation rate and short-circuit current density factors; Step 7, statistically analyzing all the calculation results of step 6, and calculating the refraction, reflectivity, carrier generation rate and short-circuit current density factor of the solar cell.

[0005] Preferably, in step 1, the materials in the solar cell include silicon, electrodes and anti-reflection films.

[0006] Preferably, in step 1, the optical parameters include a refractive index n and an extinction coefficient k.

[0007] Preferably, in step 2, the crystalline silicon photovoltaic cell structure includes an anti-reflection layer, a crystalline silicon layer and a back electrode.

[0008] Preferably, in step 2, an optical model of the solar cell is established in FDTD solution software.

[0009] Preferably, in step 6, the performance of the crystalline silicon solar cell is simulated and calculated using FDTD solution software.

[0010] Preferably, in step 3, the simulation area, the refraction and reflection monitor positions are set with reference to the structure and position of the solar cell.

[0011] Preferably, the solar cell is a crystalline silicon solar cell.

[0012] Preferably, in step 4, when setting the grid accuracy, a balance is struck between calculation time and accuracy.

[0013] More preferably, the grid precision is set to 2.

[0014] Beneficial effects of the present invention: 1. The simulation method of the present invention solves the problem of unclear efficiency loss mechanism of solar cells by modeling the model of solar cells. Finally, simulation software is used to perform simulation calculations to establish a solar cell model with a clear energy loss mechanism. From a microscopic perspective, it solves the problems of unclear planning of factors affecting battery efficiency, small dimensions, incomplete optical properties, and inaccurate analysis results, providing a solution for improving the efficiency of solar cells in photovoltaic building integration.

[0015] 2. The prediction method of the present invention can accurately and efficiently obtain the conversion efficiency of solar cells and factors affecting efficiency, and can save the time cost of analyzing the solar cell efficiency model.

[0016] 3. The prediction method of the present invention is simple and efficient, with strong practicability and scalability. It can adapt to multi-parameter variables, accurately calculate the efficiency of solar cells, provide a feasible solution for improving the efficiency of photovoltaic modules, and provide technical guidance for the large-scale application of photovoltaic building integration. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of the optical model structure of a solar cell; Figure 2 Schematic diagram of optical parameters of silicon; Figure 3 Schematic diagram of the distribution of charge carriers inside the battery; Figure 4 Schematic diagram of the electric field distribution inside the battery; Figure 5 Flowchart for parameter setting of solar cell performance simulation method based on FDTD solution. DETAILED DESCRIPTION

[0018] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0019] Embodiment 1: A method for simulating solar cell performance based on FDTD solution, comprising the following steps: Step 1, look up the optical parameters of the materials in the solar cell and input them into the material library; the materials in the solar cell include silicon, electrodes and anti-reflection films. The optical parameters include the refractive index n and the extinction coefficient k. In this embodiment, the optical parameters of each layer of different materials are substituted into the FDTD-solution simulation software, and a solar cell model with a reasonable structure and accurate data is established based on the structure of the actual solar cell and the optical parameters of each material are accurately determined; Step 2: Using the determined optical parameters as known numbers, and based on the default crystalline silicon photovoltaic cell structure, an optical model of the solar cell is established in the FDTDsolution software (e.g. Figure 1 As shown); the crystalline silicon photovoltaic cell structure includes an anti-reflection layer, a crystalline silicon layer and a back electrode.

[0020] Step 3: According to the size of the solar cell, set the simulation area around the solar cell, the refraction and reflection monitor positions and types (such as Figure 5 As shown in the figure), the simulation area, refraction and reflection monitor positions are set with reference to the structure and position of the solar cell; the incident light intensity and wavelength are set according to the sunlight; Step 4, according to the size of the solar cell, set the applied boundary conditions and set the grid accuracy to 2; the setting of boundary conditions and grid accuracy minimizes the amount of calculation while ensuring the stability of the algorithm, and strikes a balance between accuracy and efficiency (using periodicity and symmetry).

[0021] Step 5, respectively loading the monitor and boundary condition parameters set in steps 3 and 4 into the optical model of the solar cell established in step 2 to establish a complete solar cell optical model; Step 6, based on the complete solar cell optical model established in step 5 and the results of the monitor, the performance of the crystalline silicon solar cell is simulated and calculated by using FDTD solution software to analyze the carrier generation rate and short-circuit current density factors; Step 7, statistically analyzing all the calculation results of step 6, and calculating the refraction, reflectivity, carrier generation rate and short-circuit current density factor of the solar cell.

[0022] This embodiment takes the traditional crystalline silicon solar cell as an example. The known conditions in the modeling stage are: the preset crystalline silicon band gap is 1.1ev, the wavelength range of the simulated incident standard solar radiation light source (AM1.5G) is 300-1100nm, the thickness of the crystalline silicon is 200nm, and electrodes and gate lines are provided. The optical parameters of silicon vary with wavelength as shown in Figure 2 shown.

[0023] According to electromagnetic wave theory, the two Maxwell curl equations describing the electromagnetic field are: (1) Where: E is the electric field strength (V / m); H is the magnetic field intensity (A / m); D is the electric displacement vector (C / m2); B is the magnetic flux intensity (T); J is the current density (A / m2); M is the magnetic flux density (V.m2); The material equation is expressed as: (2) Where: Dielectric constant (F / m); is the magnetic permeability of the medium (H / m); is the conductivity (S / m); is the magnetic permeability(); From this we can get the Mccurl equation: (3) Based on the current size, parameters, reflection, projection, electric and magnetic field monitors, boundary conditions, and grid accuracy of solar cells, the performance parameters of solar cells are calculated, including factors such as carrier generation rate, short-circuit current density, and electric field distribution.

[0024] In this embodiment, the carrier generation distribution of the crystalline silicon solar cell is as follows: Figure 3 As shown in the figure, the carriers are concentrated in the upper part of the absorption layer, and the carriers generated in the lower part of the absorption layer are less. The maximum value is 1.53e+27. The electric field distribution is relatively uniform due to the influence of refraction and diffraction (such as Figure 4 The full-band reflectivity is 41.06%. The short-circuit current density is 13.2413 mA / cm 2 .

[0025] The prediction method of the embodiment of the present invention can solve the current problems of unclear efficiency loss mechanism in solar cells, unclear factors affecting battery efficiency, incomplete optical properties, small dimensions and long calculation time, and provide a feasible solution for improving the efficiency of solar cells.

[0026] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A solar cell performance simulation method based on FDTD solution, characterized in that: It includes the following steps: Step 1, look up the optical parameters of materials in solar cells and input them into the material library; Step 2, using the determined optical parameters as known numbers and based on a default crystalline silicon photovoltaic cell structure, an optical model of the solar cell is established; Step 3, according to the size of the solar cell, set the simulation area around the solar cell, and the position and type of the refraction and reflection monitors; Set the incident light intensity and wavelength according to sunlight; Step 4, according to the size of the solar cell, set the applied boundary conditions and set the grid accuracy; Step 5, respectively loading the monitor and boundary condition parameters set in steps 3 and 4 into the optical model of the solar cell established in step 2 to establish a complete solar cell optical model; Step 6, based on the complete solar cell optical model established in step 5 and based on the monitor results, simulate and calculate the performance of the crystalline silicon solar cell, and analyze the carrier generation rate and short-circuit current density factors; Step 7, statistically analyzing all the calculation results of step 6, and calculating the refraction, reflectivity, carrier generation rate and short-circuit current density factor of the solar cell.

2. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In step 1, the materials in the solar cell include silicon, electrodes and anti-reflection films.

3. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In step 1, the optical parameters include a refractive index n and an extinction coefficient k.

4. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In the step 2, the crystalline silicon photovoltaic cell structure includes an anti-reflection layer, a crystalline silicon layer and a back electrode.

5. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In step 2, an optical model of the solar cell is established in the FDTD solution software.

6. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In step 6, the performance of the crystalline silicon solar cell is simulated and calculated using FDTD solution software.

7. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In step 3, the simulation area, refraction, and reflection monitor positions are set with reference to the structure and position of the solar cell.

8. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: The solar cell is a crystalline silicon solar cell.

9. The method for simulating solar cell performance based on FDTD solution according to claim 1, characterized in that: In step 4, when setting the mesh accuracy, balance computation time and accuracy.

10. The method for simulating solar cell performance based on FDTD solution according to claim 9, characterized in that: Set the grid resolution to 2.

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